Chasing participation

[sinner]

This weekend I was pretty busy relaxing! But all of that relaxing did lead me to consider one idea, that it might be possible to capture "participation" as an index filter using "small universe" indexes vs "big universe" indexes. Basically, breadth in its crudest form.

I also wanted to try this with Australian data.

Most on this forum probably know of the STW ETF which tracks the ASX S&P 200 index. But, at least personally I wasn't aware that on the same day, SSGA also released another ETF, SFY, which tracks the ASX S&P 50 index.

So in this case, STW will represnt our "big universe" of stocks, to measure the participation across a basket of equities while SFY will represent the "small universe" and also act as our trading vehicle. One thing I like about large caps is that their largeness allows them to withstand the business cycle better, whereas a lot of small caps will take it in the neck on factors out of their control during a downturn.

I do realise that using a cap weighted index for the measure of participation is not optimal. But for a quick Sunday night quantification, it'll do!

Any good experiment should have some controls. So:

SFY buy+hold returns 2002-08-27 till current

                          daily.returns
Annualized Return                0.0562
Annualized Std Dev               0.1770
Annualized Sharpe (Rf=0%)        0.3174

STW buy+hold returns 2002-08-27 till current

                          daily.returns
Annualized Return                0.0509
Annualized Std Dev               0.1733
Annualized Sharpe (Rf=0%)        0.2939

SFY using SFY 120day Rate of Change > 0 as index filter:

                          daily.returns
Annualized Return                0.0491
Annualized Std Dev               0.1203
Annualized Sharpe (Rf=0%)        0.4086

SFY using SFY 180day Rate of Change > 0 as index filter:

                          daily.returns
Annualized Return                0.0608
Annualized Std Dev               0.1193
Annualized Sharpe (Rf=0%)        0.5101

SFY using SFY 240day Rate of Change > 0 as index filter:

                          daily.returns
Annualized Return                0.0640
Annualized Std Dev               0.1189
Annualized Sharpe (Rf=0%)        0.5381

I'm providing a range of lookback periods, mostly just to demonstrate that the lookback period isn't too important (i.e. you can derive the same results by any method which captures momentum/trend).

As a general rule of thumb, longer lookbacks will underperform shorter ones during bull markets and vice versa in bear markets.

Great. Nothing new to see here! Now. What happens if we add more information, about more stocks into the above crude trading system? What I mean is, what if we use STWs Rate of Change as the trend filter for SFY?

SFY using STW 120day Rate of Change > 0 as index filter:

                          daily.returns
Annualized Return                0.0767
Annualized Std Dev               0.1217
Annualized Sharpe (Rf=0%)        0.6299

SFY using STW 180day Rate of Change > 0 as index filter:

                          daily.returns
Annualized Return                0.0856
Annualized Std Dev               0.1211
Annualized Sharpe (Rf=0%)        0.7065

SFY using STW 240day Rate of Change > 0 as index filter:

                          daily.returns
Annualized Return                0.0577
Annualized Std Dev               0.1200
Annualized Sharpe (Rf=0%)        0.4807

Now, like a good scientist we will also need to test to see what happens when we using SFY as the signal for STW, to make sure we aren't crazy:

STW using SFY 120day Rate of Change > 0 as index filter:

                          daily.returns
Annualized Return                0.1206
Annualized Std Dev               0.1090
[COLOR="#FF0000"]Annualized Sharpe (Rf=0%)        1.1072[/COLOR]

STW using SFY 180day Rate of Change > 0 as index filter:

                          daily.returns
Annualized Return                0.1147
Annualized Std Dev               0.1097
[COLOR="#FF0000"]Annualized Sharpe (Rf=0%)        1.0456[/COLOR]

STW using SFY 240day Rate of Change > 0 as index filter:

                          daily.returns
Annualized Return                0.0884
Annualized Std Dev               0.1109
[COLOR="#FF0000"]Annualized Sharpe (Rf=0%)        0.7969[/COLOR]

Wow! That was unexpected! From the initial experiment, it looked like using STW as a signal for SFY was a good idea, with better Sharpe than using STW as it's own signal. However there was a little warning sign here, as the 240 day lookback did not outperform.

But then when we performed our second experiment we found that, actually, SFY is much more informative to STW than the other way around!

With our scientist hat on, our only role is to come up with some hypothesis and then test reality to see if it matches our hypothesis. If not, we can discard it and come up with a fresh one for testing.

In this case, I would hypothesise that one of two things may be occuring:
1. It is probable that the cap weighted STW is not a good measurement of participation since the top 10 stocks make up >50% of the index value. I hypothesise that a equal weight index would provide a more robust measurement of participation. Unfortunately there is no existing ETF with enough data for me to test and I don't feel like generating my own index on a Sunday night.
2. It is less likely but still probable that due to the nature of the Australian economy, the companies in the ASX S&P 50 actually are more informative about the future performance of the remainder of the market and hence outweigh any "breadth" effect.

In either case, we can derive one small conclusion: namely that using the returns of a related index seems to provide better risk adjusted returns than using the index itself.

Now this is probably as far as I'll take this idea, at least until I get the chance for more relaxation! But since I know everyone loves pictures, here are a couple:

Equity curve of most performant system tested (STW using SFY 120 ROC as signal):


Sharpes as graph:

 

[Ves]

Hi sinner, interesting read.

You could also try VAS instead of STW if you thought that the ASX 300 would be more inclusive of the wider Australian stock universe.

Am I understanding correctly that a filter like "180day Rate of Change > 0" means that in the first instance if the price action for the last 180 days is positive the index is purchased (or a continuing hold if already held) and a sell when the last 180 days switches to negative? I assume the filter is updated each trading day. It looks like it outperformed the index because the system was out of the market from roughly Feb 2008 to May 2009 (and also one of the Euro crisis events in 2011).

 

[sinner]

Hi Ves,

Would have preferred VAS but it just hasn't existed for long enough.

Your understannding of the filter is correct. Daily rebalance just for demonstration, you can do things like check the daily chart on a daily or even monthly frequency to reduce turnover.

Generally I wouldn't actually use ROC in a live system as raw trend measures are susceptible to whipsaw. David Varadi has some nice adaptations (e.g. error adjusted momentum, vol adjusted momentum, probabilistic momentum) on his CSSanalytics blog which are more appropriate for live trading.

Any reasonable trend or absolute momentum measure would have shuttled investors to cash during the timefranes you highlight, the goal here is to understand whether using measures which capture better info about participation would have added some alpha.

 

[Ves]

Some interesting ideas here...

I don't know much about this kind of thing at all, but your posts do lead to a few possibilities in my mind, especially with indexes like the ASX that are heavily concentrated by a few companies, and in some cases, in the same industry (ANZ/CBA/NAB/WBC, RIO/FMG/BHP, WOW/WES).

As you mentioned you could use an alternative to the ASX 50, a self-made index or even a themed ETF, around one of the sectors (banks, mining, supermarkets), since the ASX probably is more highly correlated to movements in those companies, than a less concentrated index like the S&P 500.

Given the rising popularity of ETFs in Australia (here's hoping liquidity and variety grows exponentially) there might be heaps more opportunity to undertake and maybe even implement some of these ideas much more easily in the coming years!

PS: the point about whip-sawing is a very good one, but I didn't want to mention it in case it led the thread to go right off-track.

 

[sinner]

Some interesting ideas here...

yup and I guess you are starting to see how investigation of ideas can be both fun and inspiring! Much less about the profit than the understanding and influence on your thinking.

PS: the point about whip-sawing is a very good one, but I didn't want to mention it in case it led the thread to go right off-track.

If you think about it you'll realise that whipsaws, buying tops, etc are just the cost of business for trend followers. I personally don't view it as a huge deal (although obviously important to mitigate as much as possible).

Fear of whipsaw is a psychological thing, in exactly the same way that buying a falling security is for contrarians. Trend trade enough and sooner or later you'll get whipsawed during a regime change or sideways market. The euro chopped wood for a whole year before its most recent collapse and as usual trading breakouts was declared dead...

Ed Seykota's Whipsaw Song
http://www.michaelcovel.com/2009/05/30/ed-seykotas-whipsaw-song/

 

[skyQuake]

Cool stuff here sinner, have you thought about using the XSO as a the signal instead of STW?